↓ Skip to main content

Calibration of the global physical activity questionnaire to Accelerometry measured physical activity and sedentary behavior

Overview of attention for article published in BMC Public Health, March 2018
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
70 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Calibration of the global physical activity questionnaire to Accelerometry measured physical activity and sedentary behavior
Published in
BMC Public Health, March 2018
DOI 10.1186/s12889-018-5310-3
Pubmed ID
Authors

Kristen M. Metcalf, Barbara I. Baquero, Mayra L. Coronado Garcia, Shelby L. Francis, Kathleen F. Janz, Helena H. Laroche, Daniel K. Sewell

Abstract

Self-report questionnaires are a valuable method of physical activity measurement in public health research; however, accuracy is often lacking. The purpose of this study is to improve the validity of the Global Physical Activity Questionnaire by calibrating it to 7 days of accelerometer measured physical activity and sedentary behavior. Participants (n = 108) wore an ActiGraph GT9X Link on their non-dominant wrist for 7 days. Following the accelerometer wear period, participants completed a telephone Global Physical Activity Questionnaire with a research assistant. Data were split into training and testing samples, and multivariable linear regression models built using functions of the GPAQ self-report data to predict ActiGraph measured physical activity and sedentary behavior. Models were evaluated with the testing sample and an independent validation sample (n = 120) using Mean Squared Prediction Errors. The prediction models utilized sedentary behavior, and moderate- and vigorous-intensity physical activity self-reported scores from the questionnaire, and participant age. Transformations of each variable, as well as break point analysis were considered. Prediction errors were reduced by 77.7-80.6% for sedentary behavior and 61.3-98.6% for physical activity by using the multivariable linear regression models over raw questionnaire scores. This research demonstrates the utility of calibrating self-report questionnaire data to objective measures to improve estimates of physical activity and sedentary behavior. It provides an understanding of the divide between objective and subjective measures, and provides a means to utilize the two methods as a unified measure.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 19%
Student > Master 12 17%
Researcher 7 10%
Student > Bachelor 6 9%
Student > Doctoral Student 4 6%
Other 11 16%
Unknown 17 24%
Readers by discipline Count As %
Medicine and Dentistry 14 20%
Sports and Recreations 11 16%
Nursing and Health Professions 6 9%
Psychology 4 6%
Neuroscience 3 4%
Other 9 13%
Unknown 23 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 March 2018.
All research outputs
#10,167,812
of 12,728,337 outputs
Outputs from BMC Public Health
#7,474
of 8,680 outputs
Outputs of similar age
#204,372
of 272,967 outputs
Outputs of similar age from BMC Public Health
#1
of 1 outputs
Altmetric has tracked 12,728,337 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,680 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 272,967 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them